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A Hybrid Multiobjective Differential Evolution Approach to Stator Winding Optimization

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Applications of Evolutionary Computation (EvoApplications 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11454))

Abstract

This paper describes a multiobjective differential evolution approach to the optimization of the design of alternating current distributed stator windings of electric motors. The objective functions are minimizing both the machine airgap magnetomotive force distortion and the winding wire length. Constraints are related to the physical feasibility of solutions. Four distinct winding types are considered. Three mutation variations of the multiobjective differential evolution algorithm are developed and assessed using different performance metrics. These algorithmic approaches are able to generate well-distributed, uniformly spread solutions on the nondominated front. The characterization of the nondominated fronts conveys helpful information for aiding design engineers to choose the most suitable compromise solution for a specific machine, embodying a balanced trade-off between machine efficiency and manufacturing cost.

A. M. Silva acknowledges the support by the Portuguese Science and Technology Foundation (FCT).

C. H. Antunes acknowledges the support of projects UID/Multi/308/2019, ESGRIDS (POCI-01-0145-FEDER-016434) and MAnAGER (POCI-01-0145-FEDER-028040).

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Author information

Authors and Affiliations

  1. ISR Coimbra, DEEC, University of Coimbra, Polo 2, 3030-290, Coimbra, Portugal

    André M. Silva & Fernando J. T. E. Ferreira

  2. INESC Coimbra, DEEC, University of Coimbra, Polo 2, 3030-290, Coimbra, Portugal

    Carlos Henggeler Antunes

  3. Department of Electrical and Computer Engineering, University of Coimbra, Polo 2, 3030-290, Coimbra, Portugal

    Fernando J. T. E. Ferreira & Carlos Henggeler Antunes

Authors
  1. André M. Silva
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  2. Fernando J. T. E. Ferreira
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  3. Carlos Henggeler Antunes
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Corresponding author

Correspondence to André M. Silva .

Editor information

Editors and Affiliations

  1. University of Mainz, Mainz, Germany

    Paul Kaufmann

  2. University of Granada, Granada, Spain

    Pedro A. Castillo

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Silva, A.M., Ferreira, F.J.T.E., Antunes, C.H. (2019). A Hybrid Multiobjective Differential Evolution Approach to Stator Winding Optimization. In: Kaufmann, P., Castillo, P. (eds) Applications of Evolutionary Computation. EvoApplications 2019. Lecture Notes in Computer Science(), vol 11454. Springer, Cham. https://doi.org/10.1007/978-3-030-16692-2_5

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  • DOI: https://doi.org/10.1007/978-3-030-16692-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16691-5

  • Online ISBN: 978-3-030-16692-2

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